IUCrJ最新文献

{"title":"Many locks to one key: N-acetyl­neuraminic acid binding to proteins","authors":"","doi":"10.1107/S2052252524005360","DOIUrl":"10.1107/S2052252524005360","url":null,"abstract":"<div><p>In structural biology, the analogy of a key (ligand) fitting a lock (protein) is commonly used to describe the binding process. In this context, we illustrate the evolutionary development of diverse locks that exhibit specific binding to a shared key: Neu5Ac. The intricate specificity of the interaction between various locks and the common key (Neu5Ac) is explored in our review.</p></div><div><p>Sialic acids play crucial roles in cell surface glycans of both eukaryotic and prokaryotic organisms, mediating various biological processes, including cell–cell interactions, development, immune response, oncogenesis and host–pathogen interactions. This review focuses on the β-anomeric form of <em>N</em>-acetyl­neuraminic acid (Neu5Ac), particularly its binding affinity towards various proteins, as elucidated by solved protein structures. Specifically, we delve into the binding mechanisms of Neu5Ac to proteins involved in sequestering and transporting Neu5Ac in Gram-negative bacteria, with implications for drug design targeting these proteins as antimicrobial agents. Unlike the initial assumptions, structural analyses revealed significant variability in the Neu5Ac binding pockets among proteins, indicating diverse evolutionary origins and binding modes. By comparing these findings with existing structures from other systems, we can effectively highlight the intricate relationship between protein structure and Neu5Ac recognition, emphasizing the need for tailored drug design strategies to inhibit Neu5Ac-binding proteins across bacterial species.</p></div>","PeriodicalId":14775,"journal":{"name":"IUCrJ","volume":"11 5","pages":"Pages 664-674"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364026/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141534373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CheckMyMetal (CMM): validating metal-binding sites in X-ray and cryo-EM data","authors":"Michal Gucwa ,&nbsp;Vanessa Bijak ,&nbsp;Heping Zheng ,&nbsp;Krzysztof Murzyn ,&nbsp;Wladek Minor","doi":"10.1107/S2052252524007073","DOIUrl":"10.1107/S2052252524007073","url":null,"abstract":"<div><p>Recent updates to <em>CheckMyMetal</em> have significantly enhanced its capability to efficiently handle large datasets, including those generated from cryo-EM structural analyses.</p></div><div><p>Identifying and characterizing metal-binding sites (MBS) within macromolecular structures is imperative for elucidating their biological functions. <em>CheckMyMetal</em> (<em>CMM</em>) is a web based tool that facilitates the interactive valid­ation of MBS in structures determined through X-ray crystallography and cryo-electron microscopy (cryo-EM). Recent updates to <em>CMM</em> have significantly enhanced its capability to efficiently handle large datasets generated from cryo-EM structural analyses. In this study, we address various challenges inherent in validating MBS within both X-ray and cryo-EM structures. Specifically, we examine the difficulties associated with accurately identifying metals and modeling their coordination environments by considering the ongoing reproducibility challenges in structural biology and the critical importance of well annotated, high-quality experimental data. <em>CMM</em> employs a sophisticated framework of rules rooted in the valence bond theory for MBS validation. We explore how <em>CMM</em> validation parameters correlate with the resolution of experimentally derived structures of macromolecules and their complexes. Additionally, we showcase the practical utility of <em>CMM</em> by analyzing a representative cryo-EM structure. Through a comprehensive examination of experimental data, we demonstrate the capability of <em>CMM</em> to advance MBS characterization and identify potential instances of metal misassignment.</p></div>","PeriodicalId":14775,"journal":{"name":"IUCrJ","volume":"11 5","pages":"Pages 871-877"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364027/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141982362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crossing length scales: X-ray approaches to studying the structure of biological materials","authors":"Tilman A. Grünewald ,&nbsp;Marianne Liebi ,&nbsp;Henrik Birkedal","doi":"10.1107/S2052252524007838","DOIUrl":"10.1107/S2052252524007838","url":null,"abstract":"<div><p>Biological materials obtain their properties through hierarchical structuring. Understanding such materials calls for multimodal and multiscale approaches. Based on two example systems, bone and shell, we discuss current analytical approaches, their capabilities and limits, and how to tie them together to fully cover the different length scales involved in understanding materials’ functions. We will further discuss advances in this area and future developments, the possible roadblocks (radiation damage, data quantity, sample preparation) and potential ways to overcome them.</p></div><div><p>Biological materials have outstanding properties. With ease, challenging mechanical, optical or electrical properties are realised from comparatively ‘humble’ building blocks. The key strategy to realise these properties is through extensive hierarchical structuring of the material from the millimetre to the nanometre scale in 3D. Though hierarchical structuring in biological materials has long been recognized, the 3D characterization of such structures remains a challenge. To understand the behaviour of materials, multimodal and multi-scale characterization approaches are needed. In this review, we outline current X-ray analysis approaches using the structures of bone and shells as examples. We show how recent advances have aided our understanding of hierarchical structures and their functions, and how these could be exploited for future research directions. We also discuss current roadblocks including radiation damage, data quantity and sample preparation, as well as strategies to address them.</p></div>","PeriodicalId":14775,"journal":{"name":"IUCrJ","volume":"11 5","pages":"Pages 708-722"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364038/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142080328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Solvent organization in the ultrahigh-resolution crystal structure of crambin at room temperature","authors":"Julian C.-H. Chen ,&nbsp;Miroslaw Gilski ,&nbsp;Changsoo Chang ,&nbsp;Dominika Borek ,&nbsp;Gerd Rosenbaum ,&nbsp;Alex Lavens ,&nbsp;Zbyszek Otwinowski ,&nbsp;Maciej Kubicki ,&nbsp;Zbigniew Dauter ,&nbsp;Mariusz Jaskolski ,&nbsp;Andrzej Joachimiak","doi":"10.1107/S2052252524007784","DOIUrl":"10.1107/S2052252524007784","url":null,"abstract":"<div><p>Using synchrotron radiation, diffraction data extending to 0.70 Å resolution were collected from crystals of the small protein crambin at room temperature (297 K), and the structure was refined with spherical-atom approximation to an <em>R</em> factor of 0.0591, revealing (i) protein regions with multiple conformations, (ii) extended water networks correlated with protein conformations and (iii) minimal radiation damage. The structure sets a standard for room-temperature refinement of macromolecular targets and provides accurate data for modeling protein–solvent interactions.</p></div><div><p>Ultrahigh-resolution structures provide unprecedented details about protein dynamics, hydrogen bonding and solvent networks. The reported 0.70 Å, room-temperature crystal structure of crambin is the highest-resolution ambient-temperature structure of a protein achieved to date. Sufficient data were collected to enable unrestrained refinement of the protein and associated solvent networks using <em>SHELXL</em>. Dynamic solvent networks resulting from alternative side-chain conformations and shifts in water positions are revealed, demonstrating that polypeptide flexibility and formation of clathrate-type structures at hydro­phobic surfaces are the key features endowing crambin crystals with extraordinary diffraction power.</p></div>","PeriodicalId":14775,"journal":{"name":"IUCrJ","volume":"11 5","pages":"Pages 649-663"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364037/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142080330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Benchmarking predictive methods for small-angle X-ray scattering from atomic coordinates of proteins using maximum likelihood consensus data","authors":"","doi":"10.1107/S205225252400486X","DOIUrl":"10.1107/S205225252400486X","url":null,"abstract":"&lt;div&gt;&lt;p&gt;Consensus small-angle X-ray scattering (SAXS) data from five proteins in solution, generated from 171 independent measurements on 12 beamlines using a maximum likelihood method, are used to benchmark computational methods for predicting SAXS profiles from atomic coordinates. The results reveal important strengths and limitations of different methods that are serving a growing community of users in applications ranging from fundamental integrative structural biology to drug discovery and development.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;p&gt;Stimulated by informal conversations at the XVII International Small Angle Scattering (SAS) conference (Traverse City, 2017), an international team of experts undertook a round-robin exercise to produce a large dataset from proteins under standard solution conditions. These data were used to generate consensus SAS profiles for xylose isomerase, urate oxidase, xylanase, lysozyme and ribonuclease A. Here, we apply a new protocol using maximum likelihood with a larger number of the contributed datasets to generate improved consensus profiles. We investigate the fits of these profiles to predicted profiles from atomic coordinates that incorporate different models to account for the contribution to the scattering of water molecules of hydration surrounding proteins in solution. Programs using an implicit, shell-type hydration layer generally optimize fits to experimental data with the aid of two parameters that adjust the volume of the bulk solvent excluded by the protein and the contrast of the hydration layer. For these models, we found the error-weighted residual differences between the model and the experiment generally reflected the subsidiary maxima and minima in the consensus profiles that are determined by the size of the protein plus the hydration layer. By comparison, all-atom solute and solvent molecular dynamics (MD) simulations are without the benefit of adjustable parameters and, nonetheless, they yielded at least equally good fits with residual differences that are less reflective of the structure in the consensus profile. Further, where MD simulations accounted for the precise solvent composition of the experiment, specifically the inclusion of ions, the modelled radius of gyration values were significantly closer to the experiment. The power of adjustable parameters to mask real differences between a model and the structure present in solution is demonstrated by the results for the conformationally dynamic ribonuclease A and calculations with pseudo-experimental data. This study shows that, while methods invoking an implicit hydration layer have the unequivocal advantage of speed, care is needed to understand the influence of the adjustable parameters. All-atom solute and solvent MD simulations are slower but are less susceptible to false positives, and can account for thermal fluctuations in atomic positions, and more accurately represent the water molecules of hydration that contribute to the scattering profile.&lt;","PeriodicalId":14775,"journal":{"name":"IUCrJ","volume":"11 5","pages":"Pages 762-779"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364021/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141579663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-enhanced X-ray diffraction analysis: towards real-time mineral phase identification and quantification","authors":"Nikolaos I. Prasianakis","doi":"10.1107/S2052252524008157","DOIUrl":"10.1107/S2052252524008157","url":null,"abstract":"<div><p>The use of convolutional neural networks can revolutionize XRD analysis by significantly reducing processing times. Demonstration against synthetic and real mineral mixture data provide a first assessment of the accuracy of such methods.</p></div>","PeriodicalId":14775,"journal":{"name":"IUCrJ","volume":"11 5","pages":"Pages 647-648"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364041/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142107580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structure–property relationship of a complex photoluminescent arylacetylide-gold(I) compound. I: a pressure-induced phase transformation caught in the act","authors":"Róża Jastrzębska ,&nbsp;Tomasz Poręba ,&nbsp;Federico Cova ,&nbsp;Daniel M. Tchoń ,&nbsp;Anna Makal","doi":"10.1107/S2052252524007681","DOIUrl":"10.1107/S2052252524007681","url":null,"abstract":"<div><p>A pressure-induced triclinic-to-monoclinic phase transition has been caught ‘in the act’ in the course of a wider series of high-pressure synchrotron diffraction experiments conducted on a moderately photoluminescent gold(I) compound. Our experiments illustrate how conducting a fast series of experiments, enabled by modern equipment at synchrotrons, can lead to an inaccurate estimation of the actual pressure of a phase transformation.</p></div><div><p>A pressure-induced triclinic-to-monoclinic phase transition has been caught ‘in the act’ over a wider series of high-pressure synchrotron diffraction experiments conducted on a large, photoluminescent organo-gold(I) compound. Here, we describe the mechanism of this single-crystal-to-single-crystal phase transition, the onset of which occurs at ∼0.6 GPa, and we report a high-quality structure of the new monoclinic phase, refined using aspherical atomic scattering factors. Our case illustrates how conducting a fast series of diffraction experiments, enabled by modern equipment at synchrotron facilities, can lead to overestimation of the actual pressure of a phase transition due to slow transformation kinetics.</p></div>","PeriodicalId":14775,"journal":{"name":"IUCrJ","volume":"11 5","pages":"Pages 737-743"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364033/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142043945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging length scales in hard materials with ultra-small angle X-ray scattering – a critical review","authors":"Fan Zhang ,&nbsp;Jan Ilavsky","doi":"10.1107/S2052252524006298","DOIUrl":"10.1107/S2052252524006298","url":null,"abstract":"<div><p>This review examines the use of ultra-small angle X-ray scattering (USAXS), a nondestructive technique for analyzing the multi-scale microstructures of hard materials such as ceramics, metals and composites. It discusses the principles, benefits and challenges of USAXS, along with its potential to advance materials development and optimize manufacturing processes, while also considering future enhancements through multimodal characterization and machine learning.</p></div><div><p>Owing to their exceptional properties, hard materials such as advanced ceramics, metals and composites have enormous economic and societal value, with applications across numerous industries. Understanding their microstructural characteristics is crucial for enhancing their performance, materials development and unleashing their potential for future innovative applications. However, their microstructures are unambiguously hierarchical and typically span several length scales, from sub-ångstrom to micrometres, posing demanding challenges for their characterization, especially for <em>in situ</em> characterization which is critical to understanding the kinetic processes controlling microstructure formation. This review provides a comprehensive description of the rapidly developing technique of ultra-small angle X-ray scattering (USAXS), a nondestructive method for probing the nano-to-micrometre scale features of hard materials. USAXS and its complementary techniques, when developed for and applied to hard materials, offer valuable insights into their porosity, grain size, phase composition and inhomogeneities. We discuss the fundamental principles, instrumentation, advantages, challenges and global status of USAXS for hard materials. Using selected examples, we demonstrate the potential of this technique for unveiling the microstructural characteristics of hard materials and its relevance to advanced materials development and manufacturing process optimization. We also provide our perspective on the opportunities and challenges for the continued development of USAXS, including multimodal characterization, coherent scattering, time-resolved studies, machine learning and autonomous experiments. Our goal is to stimulate further implementation and exploration of USAXS techniques and inspire their broader adoption across various domains of hard materials science, thereby driving the field toward discoveries and further developments.</p></div>","PeriodicalId":14775,"journal":{"name":"IUCrJ","volume":"11 5","pages":"Pages 675-694"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364042/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141859755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phase quantification using deep neural network processing of XRD patterns","authors":"Titouan Simonnet ,&nbsp;Sylvain Grangeon ,&nbsp;Francis Claret ,&nbsp;Nicolas Maubec ,&nbsp;Mame Diarra Fall ,&nbsp;Rachid Harba ,&nbsp;Bruno Galerne","doi":"10.1107/S2052252524006766","DOIUrl":"10.1107/S2052252524006766","url":null,"abstract":"<div><p>A deep neural network approach to the identification and quantification of powder X-ray diffraction patterns was applied and proved successful for the quantitative description of complex mineralogical assemblages consisting of up to four minerals with different structures, including different space groups, for which data augmentation is not straightforward.</p></div><div><p>Mineral identification and quantification are key to the understanding and, hence, the capacity to predict material properties. The method of choice for mineral quantification is powder X-ray diffraction (XRD), generally using a Rietveld refinement approach. However, a successful Rietveld refinement requires preliminary identification of the phases that make up the sample. This is generally carried out manually, and this task becomes extremely long or virtually impossible in the case of very large datasets such as those from synchrotron X-ray diffraction computed tomography. To circumvent this issue, this article proposes a novel neural network (NN) method for automating phase identification and quantification. An XRD pattern calculation code was used to generate large datasets of synthetic data that are used to train the NN. This approach offers significant advantages, including the ability to construct databases with a substantial number of XRD patterns and the introduction of extensive variability into these patterns. To enhance the performance of the NN, a specifically designed loss function for proportion inference was employed during the training process, offering improved efficiency and stability compared with traditional functions. The NN, trained exclusively with synthetic data, proved its ability to identify and quantify mineral phases on synthetic and real XRD patterns. Trained NN errors were equal to 0.5% for phase quantification on the synthetic test set, and 6% on the experimental data, in a system containing four phases of contrasting crystal structures (calcite, gibbsite, dolomite and hematite). The proposed method is freely available on GitHub and allows for major advances since it can be applied to any dataset, regardless of the mineral phases present.</p></div>","PeriodicalId":14775,"journal":{"name":"IUCrJ","volume":"11 5","pages":"Pages 859-870"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364039/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141916724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the structure refinement of metal complexes against 3D electron diffraction data using multipolar scattering factors","authors":"Laura Pacoste ,&nbsp;Vladislav Mikhailovich Ignat’ev ,&nbsp;Paulina Maria Dominiak ,&nbsp;Xiaodong Zou","doi":"10.1107/S2052252524006730","DOIUrl":"10.1107/S2052252524006730","url":null,"abstract":"&lt;div&gt;&lt;p&gt;We apply for the first time the transferable aspherical atom model (TAAM) for the refinement of a metal complex structure against 3D ED data. Our results show that TAAM significantly outperforms the independent atom model (IAM) by more accurately depicting the electrostatic potential, particularly in low-resolution ranges. We found that using TAAM for organic ligands is more important than an accurate description of the metal centre in the refinement against 3D ED data.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;p&gt;This study examines various methods for modelling the electron density and, thus, the electrostatic potential of an organometallic complex for use in crystal structure refinement against 3D electron diffraction (ED) data. It focuses on modelling the scattering factors of iron(III), considering the electron density distribution specific for coordination with organic linkers. We refined the structural model of the metal–organic complex, iron(III) acetyl­acetonate (FeAcAc), using both the independent atom model (IAM) and the transferable aspherical atom model (TAAM). TAAM refinement initially employed multipolar parameters from the MATTS databank for acetyl­acetonate, while iron was modelled with a spherical and neutral approach (TAAM ligand). Later, custom-made TAAM scattering factors for Fe—O coordination were derived from DFT calculations [TAAM-ligand-Fe(III)]. Our findings show that, in this compound, the TAAM scattering factor corresponding to Fe&lt;sup&gt;3+&lt;/sup&gt; has a lower scattering amplitude than the Fe&lt;sup&gt;3+&lt;/sup&gt; charged scattering factor described by IAM. When using scattering factors corresponding to the oxidation state of iron, IAM inaccurately represents electrostatic potential maps and overestimates the scattering potential of the iron. In addition, TAAM significantly improved the fitting of the model to the data, shown by improved &lt;em&gt;R&lt;/em&gt;&lt;sub&gt;1&lt;/sub&gt; values, goodness-of-fit (GooF) and reduced noise in the Fourier difference map (based on the residual distribution analysis). For 3D ED, &lt;em&gt;R&lt;/em&gt;&lt;sub&gt;1&lt;/sub&gt; values improved from 19.36% (IAM) to 17.44% (TAAM-ligand) and 17.49% (TAAM-ligand-Fe&lt;sup&gt;3+&lt;/sup&gt;), and for single-crystal X-ray diffraction (SCXRD) from 3.82 to 2.03% and 1.98%, respectively. For 3D ED, the most significant &lt;em&gt;R&lt;/em&gt;&lt;sub&gt;1&lt;/sub&gt; reductions occurred in the low-resolution region (8.65–2.00 Å), dropping from 20.19% (IAM) to 14.67% and 14.89% for TAAM-ligand and TAAM-ligand-Fe(III), respectively, with less improvement in high-resolution ranges (2.00–0.85 Å). This indicates that the major enhancements are due to better scattering modelling in low-resolution zones. Furthermore, when using TAAM instead of IAM, there was a noticeable improvement in the shape of the thermal ellipsoids, which more closely resembled those of an SCXRD-refined model. This study demonstrates the applicability of more sophisticated scattering factors to improve the refinement of metal–organic complexes against 3D ED data, suggesting the need for more a","PeriodicalId":14775,"journal":{"name":"IUCrJ","volume":"11 5","pages":"Pages 878-890"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364031/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141987916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}